{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\diete\Box Sync\Werkdocumenten\Doctoraat\Papers-rapporten\Paper voting at 16 - political engagement\R&R 2\Analyses\Replication materials\Logfile.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}21 Jan 2020, 20:55:46

{com}. do "C:\Users\diete\Box Sync\Werkdocumenten\Doctoraat\Papers-rapporten\Paper voting at 16 - political engagement\R&R 2\Analyses\Replication materials\Replication_analyses.do"
{txt}
{com}. 
. **************************************************************************************************
. ** Title:               Voting at 16: Does Lowering the Voting Age Lead to More Political Engagement?   **
. **                              Evidence from a Quasi-Experiment in the City of Ghent (Belgium)                                 **
. ** Authors:             Dieter Stiers, Marc Hooghe, Ruth Dassonneville                                                                  **
. ** Data set:    Data_for_replication                                                                                                                    **
. ** Date:                December 2019                                                                                                                                   **
. **************************************************************************************************
. 
. /* NOTE: To run the dofile, it is necessary to
> install the ado's "rdrobust" and "rddensity"    */
. 
. 
. ***Load data
. use "Data_for_replication.dta" , clear
{txt}
{com}. 
. set more off
{txt}
{com}. 
. *******************
. ***Main analyses***
. *******************
. 
. *** RD analyses (Table 2)
. //Collapse data set
. collapse (mean) Attention_politics_general Talk_general Knowledge Internal_efficacy External_efficacy Trust Age_16 Age_18, by(Birthdate)
{txt}
{com}. ***16-year-olds
. *Attention to politics in general
. rdrobust Attention_politics_general Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1278
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      281{col 34}      997{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       79{col 34}       75{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  101.646{col 34}  101.646
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  183.662{col 34}  183.662
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.553{col 34}    0.553

Outcome: Attention_politics_general. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .13678{col 33} .06341{col 43}2.1571{col 52}0.031{col 60}   .0125{col 73} .261053
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .16519{col 33} .06341{col 43}2.6053{col 52}0.009{col 60} .040918{col 73} .289471
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .16519{col 33} .07102{col 43}2.3260{col 52}0.020{col 60} .025998{col 73}  .30439
{txt}{hline 19}{c BT}{hline 60}

{com}. *Talking about politics with parents/friends
. rdrobust Talk_general Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1279
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      282{col 34}      997{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      115{col 34}      109{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  152.200{col 34}  152.200
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  230.173{col 34}  230.173
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.661{col 34}    0.661

Outcome: Talk_general. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .09915{col 33} .05956{col 43}1.6646{col 52}0.096{col 60}-.017595{col 73} .215888
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .10842{col 33} .05956{col 43}1.8202{col 52}0.069{col 60}-.008323{col 73} .225161
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .10842{col 33} .07033{col 43}1.5416{col 52}0.123{col 60}-.029427{col 73} .246265
{txt}{hline 19}{c BT}{hline 60}

{com}. *Political knowledge
. rdrobust Knowledge Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1282
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      282{col 34}     1000{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       82{col 34}       77{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  103.091{col 34}  103.091
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  163.313{col 34}  163.313
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.631{col 34}    0.631

Outcome: Knowledge. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .06096{col 33} .08732{col 43}0.6981{col 52}0.485{col 60}-.110181{col 73} .232097
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .0382{col 33} .08732{col 43}0.4375{col 52}0.662{col 60}-.132939{col 73} .209339
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .0382{col 33} .10222{col 43}0.3737{col 52}0.709{col 60}-.162143{col 73} .238543
{txt}{hline 19}{c BT}{hline 60}

{com}. *Internal political efficacy
. rdrobust Internal_efficacy Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1251
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      278{col 34}      973{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       91{col 34}       89{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  119.248{col 34}  119.248
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  177.942{col 34}  177.942
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.670{col 34}    0.670

Outcome: Internal_efficacy. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .06028{col 33} .05231{col 43}1.1524{col 52}0.249{col 60}-.042243{col 73} .162794
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .07191{col 33} .05231{col 43}1.3748{col 52}0.169{col 60} -.03061{col 73} .174427
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .07191{col 33}  .0618{col 43}1.1636{col 52}0.245{col 60}-.049214{col 73}  .19303
{txt}{hline 19}{c BT}{hline 60}

{com}. *External political efficacy
. rdrobust External_efficacy Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1254
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      277{col 34}      977{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       94{col 34}       91{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  124.177{col 34}  124.177
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  177.945{col 34}  177.945
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.698{col 34}    0.698

Outcome: External_efficacy. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03876{col 33}  .0441{col 43}-0.8790{col 52}0.379{col 60}-.125187{col 73} .047666
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03403{col 33}  .0441{col 43}-0.7717{col 52}0.440{col 60}-.120456{col 73} .052397
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03403{col 33} .05222{col 43}-0.6517{col 52}0.515{col 60}-.136372{col 73} .068313
{txt}{hline 19}{c BT}{hline 60}

{com}. *Political trust
. rdrobust Trust Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1224
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      268{col 34}      956{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      126{col 34}      117{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  171.737{col 34}  171.737
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  246.900{col 34}  246.900
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.696{col 34}    0.696

Outcome: Trust. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.02832{col 33} .04446{col 43}-0.6369{col 52}0.524{col 60}-.115461{col 73} .058826
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02573{col 33} .04446{col 43}-0.5786{col 52}0.563{col 60} -.11287{col 73} .061416
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02573{col 33}  .0529{col 43}-0.4864{col 52}0.627{col 60}-.129401{col 73} .077946
{txt}{hline 19}{c BT}{hline 60}

{com}. 
. ***18-year-olds
. *Attention to politics in general
. rdrobust Attention_politics_general Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1278
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      802{col 34}      476{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      167{col 34}      160{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  235.909{col 34}  235.909
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  417.069{col 34}  417.069
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.566{col 34}    0.566

Outcome: Attention_politics_general. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .11794{col 33} .06318{col 43}1.8666{col 52}0.062{col 60}-.005896{col 73} .241776
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .1394{col 33} .06318{col 43}2.2063{col 52}0.027{col 60} .015565{col 73} .263238
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .1394{col 33} .07272{col 43}1.9169{col 52}0.055{col 60}-.003134{col 73} .281937
{txt}{hline 19}{c BT}{hline 60}

{com}. *Talking about politics with parents/friends
. rdrobust Talk_general Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1279
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      802{col 34}      477{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      212{col 34}      204{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  297.502{col 34}  297.502
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  455.506{col 34}  455.506
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.653{col 34}    0.653

Outcome: Talk_general. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.05758{col 33} .06295{col 43}-0.9148{col 52}0.360{col 60}-.180952{col 73} .065791
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.06438{col 33} .06295{col 43}-1.0228{col 52}0.306{col 60}-.187751{col 73} .058991
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.06438{col 33} .07652{col 43}-0.8413{col 52}0.400{col 60}-.214363{col 73} .085603
{txt}{hline 19}{c BT}{hline 60}

{com}. *Political knowledge
. rdrobust Knowledge Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1282
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      803{col 34}      479{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      159{col 34}      150{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  223.813{col 34}  223.813
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  378.031{col 34}  378.031
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.592{col 34}    0.592

Outcome: Knowledge. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .10991{col 33} .07425{col 43}1.4802{col 52}0.139{col 60}-.035626{col 73} .255447
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .1296{col 33} .07425{col 43}1.7453{col 52}0.081{col 60}-.015939{col 73} .275133
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .1296{col 33} .08766{col 43}1.4784{col 52}0.139{col 60}-.042212{col 73} .301406
{txt}{hline 19}{c BT}{hline 60}

{com}. *Internal political efficacy
. rdrobust Internal_efficacy Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1251
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      786{col 34}      465{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      187{col 34}      183{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  274.586{col 34}  274.586
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  460.201{col 34}  460.201
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.597{col 34}    0.597

Outcome: Internal_efficacy. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .10128{col 33} .04627{col 43}2.1888{col 52}0.029{col 60} .010589{col 73} .191968
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .11545{col 33} .04627{col 43}2.4950{col 52}0.013{col 60} .024756{col 73} .206135
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .11545{col 33} .05411{col 43}2.1337{col 52}0.033{col 60}   .0094{col 73} .221491
{txt}{hline 19}{c BT}{hline 60}

{com}. *External political efficacy
. rdrobust External_efficacy Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1254
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      786{col 34}      468{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      165{col 34}      160{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  240.831{col 34}  240.831
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  385.370{col 34}  385.370
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625

Outcome: External_efficacy. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03498{col 33} .04184{col 43}-0.8359{col 52}0.403{col 60}-.116989{col 73} .047034
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.03723{col 33} .04184{col 43}-0.8897{col 52}0.374{col 60} -.11924{col 73} .044783
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.03723{col 33} .05079{col 43}-0.7330{col 52}0.464{col 60}-.136769{col 73} .062312
{txt}{hline 19}{c BT}{hline 60}

{com}. *Political trust
. rdrobust Trust Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1224
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      763{col 34}      461{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      136{col 34}      130{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  200.954{col 34}  200.954
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  337.735{col 34}  337.735
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.595{col 34}    0.595

Outcome: Trust. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .05667{col 33} .04989{col 43}1.1360{col 52}0.256{col 60}-.041105{col 73} .154447
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .06832{col 33} .04989{col 43}1.3694{col 52}0.171{col 60}-.029461{col 73} .166091
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .06832{col 33} .05941{col 43}1.1500{col 52}0.250{col 60}-.048119{col 73} .184749
{txt}{hline 19}{c BT}{hline 60}

{com}. 
. *** RD Plot (Figure 1) ***
. //Attention to politics
. rdplot Attention_politics_general Age_16 if Age_16>-102&Age_16<102 , c(0) ci(95) shade nbins(102 102) ///
> graph_options(scheme(lean1) legend(off) xlabel(-100(50)100) ylabel(0 1) title("16-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f1, replace))      
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       154
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}       79{col 37}       75
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}       79{col 37}       75
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  101.000{col 37}  101.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: Attention_politics_general. Running variable: Age_16.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      102{col 37}      102
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.990{col 37}    0.990
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.990{col 37}    0.990
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        6
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}        8{col 37}        7
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   20.400{col 37}   17.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. rdplot Attention_politics_general Age_18 if Age_18>-236&Age_18<236 , c(0) ci(95) shade nbins(236 236) ///
> graph_options(scheme(lean1) legend(off) xlabel(-200(100)200) ylabel(0 1) title("18-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f2, replace))      
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       327
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      167{col 37}      160
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      167{col 37}      160
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  235.000{col 37}  235.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: Attention_politics_general. Running variable: Age_18.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      236{col 37}      236
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.996{col 37}    0.996
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.996{col 37}    0.996
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        8
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       10{col 37}       11
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   47.200{col 37}   29.500
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. graph combine f1 f2 , scheme(lean1) xsize(7) title("Attention to politics" , size(small)) name(F1, replace)
{res}{txt}
{com}.                 
. //Talking about politics
. rdplot Talk_general Age_16 if Age_16>-152&Age_16<152 , c(0) ci(95) shade nbins(152 152) ///
> graph_options(scheme(lean1) legend(off) xlabel(-150(50)150) ylabel(0 1) title("16-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f1, replace))
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       223
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      115{col 37}      108
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      115{col 37}      108
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  150.000{col 37}  151.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: Talk_general. Running variable: Age_16.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      152{col 37}      152
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.987{col 37}    0.993
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.987{col 37}    0.993
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        4{col 37}        3
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       10{col 37}        8
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   38.000{col 37}   50.667
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. rdplot Talk_general Age_18 if Age_18>-298&Age_18<298 , c(0) ci(95) shade nbins(298 298) ///
> graph_options(scheme(lean1) legend(off) xlabel(-250(250)250) ylabel(0 1) title("18-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f2, replace)) 
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       416
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      212{col 37}      204
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      212{col 37}      204
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  296.000{col 37}  297.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: Talk_general. Running variable: Age_18.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      298{col 37}      298
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.993{col 37}    0.997
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.993{col 37}    0.997
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        4{col 37}        3
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       12{col 37}       11
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   74.500{col 37}   99.333
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. graph combine f1 f2 , scheme(lean1) xsize(7) title("Talking about politics" , size(small)) name(F2, replace)
{res}{txt}
{com}.         
. //Political knowledge
. rdplot Knowledge Age_16 if Age_16>-103&Age_16<103 , c(0) ci(95) shade nbins(103 103) ///
> graph_options(scheme(lean1) legend(off) xlabel(-100(50)100) ylabel(0 1) title("16-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f1, replace))
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       157
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}       81{col 37}       76
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}       81{col 37}       76
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  102.000{col 37}  102.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: Knowledge. Running variable: Age_16.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      103{col 37}      103
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.990{col 37}    0.990
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.990{col 37}    0.990
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        8{col 37}        4
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}        9{col 37}        6
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   12.875{col 37}   25.750
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. rdplot Knowledge Age_18 if Age_18>-224&Age_18<224 , c(0) ci(95) shade nbins(224 224) ///
> graph_options(scheme(lean1) legend(off) xlabel(-200(100)200) ylabel(0 1) title("18-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f2, replace)) 
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       309
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      159{col 37}      150
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      159{col 37}      150
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  223.000{col 37}  223.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: Knowledge. Running variable: Age_18.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      224{col 37}      224
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.996{col 37}    0.996
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.996{col 37}    0.996
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       11{col 37}        9
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   56.000{col 37}   56.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. graph combine f1 f2 , scheme(lean1) xsize(7) title("Political knowledge" , size(small)) name(F3, replace)
{res}{txt}
{com}. 
. //Create Figure 1
. graph combine F1 F2 F3 , scheme(lean1) col(1) ysize(10)
{res}{txt}
{com}. //Save Figure
. graph export "Figure_1.pdf", as(pdf) replace
{txt}(file Figure_1.pdf written in PDF format)

{com}. 
. ****************
. ***Appendices***
. ****************
. 
. *** Appendix A ***
. *Load data
. use "Data_for_replication.dta" , clear
{txt}
{com}. *Factor analysis political trust
. factor Trust_NatParl Trust_NatGov Trust_politicians Trust_polparties
{txt}(obs=2142)

Factor analysis/correlation{col 52}Number of obs    = {res}    2142
{col 5}{txt}Method: principal factors{col 52}Retained factors = {res}       2
{col 5}{txt}Rotation: (unrotated){col 52}Number of params = {res}       6

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      2.82651      2.46606            0.9510       0.9510
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.36045      0.43977            0.1213       1.0722
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}     -0.07932      0.05608           -0.0267       1.0456
{txt}{col 5}{ralign 11:Factor4}  {c |}{res}     -0.13540            .           -0.0456       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}6{txt})  ={res} 7044.83{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:Trust_NatP~l}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.8894}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.2775}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.1320}}}{space 1}
{space 4}{space 0}{ralign 12:Trust_NatGov}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.8832}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.2884}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.1368}}}{space 1}
{space 4}{space 0}{ralign 12:Trust_poli~s}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7943}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.3148}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.2700}}}{space 1}
{space 4}{space 0}{ralign 12:Trust_polp~s}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7903}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.3181}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.2742}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{c  BT}{hline 14}

{com}. alpha Trust_NatParl Trust_NatGov Trust_politicians Trust_polparties

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} 2.781773
{txt}Number of items in the scale:{col 34}{res}        4
{txt}Scale reliability coefficient:{col 34}{res}   0.8974
{txt}
{com}. 
. *Table A.1
. sum Attention_politics_general Talk_general Knowledge Internal_efficacy External_efficacy Trust

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
Attention_~l {c |}{res}      2341    .4477431    .2701926          0          1
{txt}Talk_general {c |}{res}      2333     .592156    .2865778          0          1
{txt}{space 3}Knowledge {c |}{res}      2360    .5308475    .3159691          0          1
{txt}Internal_e~y {c |}{res}      2249    .4581851    .2044794          0          1
{txt}External_e~y {c |}{res}      2247    .4982693    .1865023          0          1
{txt}{hline 13}{c +}{hline 56}
{space 7}Trust {c |}{res}      2142    .5240313    .1760107          0          1
{txt}
{com}. 
. *** Appendix B ***
. *Load data
. use "Data_for_replication.dta" , clear
{txt}
{com}. *Collapse data
. collapse (mean) Online Intended Age_16 Age_18, by(Birthdate)
{txt}
{com}. *Analyses Table B.1
. //16-year-olds
. rdrobust Online Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1275
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      280{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      129{col 34}      124{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  170.915{col 34}  170.915
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  255.004{col 34}  255.004
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.670{col 34}    0.670

Outcome: Online. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00873{col 33} .04956{col 43}-0.1761{col 52}0.860{col 60} -.10586{col 73} .088407
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00295{col 33} .04956{col 43}-0.0595{col 52}0.953{col 60}-.100081{col 73} .094185
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00295{col 33} .05963{col 43}-0.0494{col 52}0.961{col 60}-.119826{col 73}  .11393
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Intended Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1254
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      275{col 34}      979{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       89{col 34}       89{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  118.302{col 34}  118.302
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  186.600{col 34}  186.600
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.634{col 34}    0.634

Outcome: Intended. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .01854{col 33} .06865{col 43}0.2701{col 52}0.787{col 60}-.116007{col 73} .153095
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .04223{col 33} .06865{col 43}0.6152{col 52}0.538{col 60}-.092319{col 73} .176783
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .04223{col 33} .07902{col 43}0.5345{col 52}0.593{col 60}-.112637{col 73} .197101
{txt}{hline 19}{c BT}{hline 60}

{com}. //18-year-olds
. rdrobust Online Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1275
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      800{col 34}      475{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      194{col 34}      186{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  273.052{col 34}  273.052
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  418.978{col 34}  418.978
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.652{col 34}    0.652

Outcome: Online. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .05663{col 33} .04315{col 43}1.3123{col 52}0.189{col 60}-.027949{col 73} .141211
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .04864{col 33} .04315{col 43}1.1272{col 52}0.260{col 60}-.035939{col 73} .133222
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .04864{col 33} .05101{col 43}0.9536{col 52}0.340{col 60}-.051328{col 73} .148611
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Intended Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1254
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      785{col 34}      469{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      183{col 34}      175{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  263.039{col 34}  263.039
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  400.795{col 34}  400.795
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.656{col 34}    0.656

Outcome: Intended. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04891{col 33} .04693{col 43}-1.0421{col 52}0.297{col 60}-.140888{col 73} .043073
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0553{col 33} .04693{col 43}-1.1784{col 52}0.239{col 60}-.147282{col 73}  .03668
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0553{col 33}  .0563{col 43}-0.9823{col 52}0.326{col 60}-.165644{col 73} .055042
{txt}{hline 19}{c BT}{hline 60}

{com}. 
. *** Appendix C ***
. *Load data
. use "Data_for_replication.dta" , clear
{txt}
{com}. ***Number of observations (Table C.1)
. tab Age_16 if Age_16>-6&Age_16<6

     {txt}Age_16 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
         -5 {c |}{res}          1        5.88        5.88
{txt}         -4 {c |}{res}          1        5.88       11.76
{txt}         -3 {c |}{res}          3       17.65       29.41
{txt}         -2 {c |}{res}          1        5.88       35.29
{txt}         -1 {c |}{res}          1        5.88       41.18
{txt}          0 {c |}{res}          1        5.88       47.06
{txt}          1 {c |}{res}          2       11.76       58.82
{txt}          2 {c |}{res}          2       11.76       70.59
{txt}          4 {c |}{res}          2       11.76       82.35
{txt}          5 {c |}{res}          3       17.65      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}         17      100.00
{txt}
{com}. tab Age_18 if Age_18>-6&Age_18<6

     {txt}Age_18 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
         -5 {c |}{res}          1       10.00       10.00
{txt}         -3 {c |}{res}          2       20.00       30.00
{txt}         -1 {c |}{res}          1       10.00       40.00
{txt}          1 {c |}{res}          4       40.00       80.00
{txt}          3 {c |}{res}          1       10.00       90.00
{txt}          4 {c |}{res}          1       10.00      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}         10      100.00
{txt}
{com}. 
. ***RD models using raw data (Table C.2)
. //16-year-olds
. rdrobust Attention_politics_general Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2281
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      571{col 34}     1710{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      148{col 34}      116{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}   90.318{col 34}   90.318
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  169.149{col 34}  169.149
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.534{col 34}    0.534

Outcome: Attention_politics_general. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .13451{col 33} .06186{col 43}2.1746{col 52}0.030{col 60} .013278{col 73} .255751
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .16108{col 33} .06186{col 43}2.6042{col 52}0.009{col 60} .039848{col 73} .282321
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .16108{col 33} .06918{col 43}2.3285{col 52}0.020{col 60} .025497{col 73} .296673
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Talk_general Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2273
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      570{col 34}     1703{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      203{col 34}      171{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  137.172{col 34}  137.172
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  207.498{col 34}  207.498
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.661{col 34}    0.661

Outcome: Talk_general. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .12677{col 33} .06497{col 43}1.9511{col 52}0.051{col 60}-.000578{col 73} .254109
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .1357{col 33} .06497{col 43}2.0885{col 52}0.037{col 60} .008352{col 73}  .26304
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .1357{col 33} .07691{col 43}1.7643{col 52}0.078{col 60}-.015045{col 73} .286437
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Knowledge Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2296
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      574{col 34}     1722{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      188{col 34}      159{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  121.477{col 34}  121.477
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  178.483{col 34}  178.483
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.681{col 34}    0.681

Outcome: Knowledge. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .05393{col 33} .07663{col 43}0.7038{col 52}0.482{col 60}-.096256{col 73} .204118
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .04423{col 33} .07663{col 43}0.5773{col 52}0.564{col 60}-.105952{col 73} .194422
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .04423{col 33} .09085{col 43}0.4869{col 52}0.626{col 60}-.133821{col 73}  .22229
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Internal_efficacy Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2193
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      546{col 34}     1647{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      191{col 34}      163{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  134.736{col 34}  134.736
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  216.106{col 34}  216.106
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.623{col 34}    0.623

Outcome: Internal_efficacy. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .05231{col 33} .04383{col 43}1.1935{col 52}0.233{col 60}-.033593{col 73} .138221
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .06567{col 33} .04383{col 43}1.4982{col 52}0.134{col 60}-.020238{col 73} .151575
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .06567{col 33} .05051{col 43}1.3002{col 52}0.194{col 60}-.033324{col 73} .164661
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust External_efficacy Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2190
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      542{col 34}     1648{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      207{col 34}      176{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  144.862{col 34}  144.862
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  211.584{col 34}  211.584
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.685{col 34}    0.685

Outcome: External_efficacy. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.04361{col 33} .04201{col 43}-1.0379{col 52}0.299{col 60}-.125952{col 73} .038741
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.04582{col 33} .04201{col 43}-1.0906{col 52}0.275{col 60}-.128165{col 73} .036527
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.04582{col 33} .04997{col 43}-0.9169{col 52}0.359{col 60}-.143758{col 73} .052119
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Trust Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2089
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      513{col 34}     1576{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      236{col 34}      197{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  170.673{col 34}  170.673
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  259.585{col 34}  259.585
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.657{col 34}    0.657

Outcome: Trust. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.01786{col 33} .03546{col 43}-0.5037{col 52}0.614{col 60}-.087357{col 73} .051638
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} -.0123{col 33} .03546{col 43}-0.3470{col 52}0.729{col 60}  -.0818{col 73} .057195
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} -.0123{col 33} .04237{col 43}-0.2904{col 52}0.772{col 60}-.095346{col 73} .070741
{txt}{hline 19}{c BT}{hline 60}

{com}. 
. //18-year-olds
. rdrobust Attention_politics_general Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2281
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1463{col 34}      818{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      332{col 34}      328{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  275.966{col 34}  275.966
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  485.978{col 34}  485.978
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.568{col 34}    0.568

Outcome: Attention_politics_general. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08191{col 33}  .0478{col 43}1.7138{col 52}0.087{col 60}-.011766{col 73}  .17559
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09819{col 33}  .0478{col 43}2.0544{col 52}0.040{col 60} .004515{col 73} .191871
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09819{col 33} .05557{col 43}1.7671{col 52}0.077{col 60}-.010718{col 73} .207104
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Talk_general Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2273
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1457{col 34}      816{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      330{col 34}      329{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  275.975{col 34}  275.975
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  441.085{col 34}  441.085
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.626{col 34}    0.626

Outcome: Talk_general. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.08098{col 33} .05442{col 43}-1.4881{col 52}0.137{col 60} -.18763{col 73} .025679
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.09402{col 33} .05442{col 43}-1.7277{col 52}0.084{col 60}-.200671{col 73} .012638
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.09402{col 33} .06499{col 43}-1.4466{col 52}0.148{col 60}-.221401{col 73} .033367
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Knowledge Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2296
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1471{col 34}      825{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      262{col 34}      255{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  217.579{col 34}  217.579
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  348.168{col 34}  348.168
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.625{col 34}    0.625

Outcome: Knowledge. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .08313{col 33} .06714{col 43}1.2381{col 52}0.216{col 60}-.048469{col 73}  .21472
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .09619{col 33} .06714{col 43}1.4327{col 52}0.152{col 60}  -.0354{col 73} .227788
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .09619{col 33} .07982{col 43}1.2051{col 52}0.228{col 60}-.060259{col 73} .252646
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Internal_efficacy Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2193
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1404{col 34}      789{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      370{col 34}      363{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  321.214{col 34}  321.214
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  517.644{col 34}  517.644
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.621{col 34}    0.621

Outcome: Internal_efficacy. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .06324{col 33} .03315{col 43}1.9078{col 52}0.056{col 60}-.001728{col 73} .128201
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .07121{col 33} .03315{col 43}2.1484{col 52}0.032{col 60} .006245{col 73} .136174
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .07121{col 33} .03919{col 43}1.8173{col 52}0.069{col 60}-.005592{col 73} .148011
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust External_efficacy Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2190
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1400{col 34}      790{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      265{col 34}      260{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  229.176{col 34}  229.176
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  357.888{col 34}  357.888
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.640{col 34}    0.640

Outcome: External_efficacy. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00811{col 33} .03909{col 43}-0.2074{col 52}0.836{col 60}-.084728{col 73} .068514
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00757{col 33} .03909{col 43}-0.1935{col 52}0.847{col 60}-.084186{col 73} .069056
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00757{col 33}  .0473{col 43}-0.1600{col 52}0.873{col 60}-.100263{col 73} .085132
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Trust Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      2089
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1321{col 34}      768{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      228{col 34}      231{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  207.541{col 34}  207.541
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  326.101{col 34}  326.101
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.636{col 34}    0.636

Outcome: Trust. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .04632{col 33} .04455{col 43}1.0398{col 52}0.298{col 60}-.040993{col 73} .133642
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .05337{col 33} .04455{col 43}1.1979{col 52}0.231{col 60}-.033949{col 73} .140685
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .05337{col 33} .05391{col 43}0.9899{col 52}0.322{col 60}-.052302{col 73} .159038
{txt}{hline 19}{c BT}{hline 60}

{com}. 
. ***Test for selection bias
. *Load data
. use "Population_data.dta" , clear
{txt}
{com}. *T-tests (Table C.3)
. ttest Age_corr , by(PART)

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}   8654{col 22} 16.98186{col 34} .0154134{col 46} 1.433859{col 58} 16.95164{col 70} 17.01207
       {txt}1 {c |}{res}{col 12}   2359{col 22} 16.87707{col 34} .0295778{col 46}  1.43658{col 58} 16.81907{col 70} 16.93507
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12}  11013{col 22} 16.95941{col 34} .0136743{col 46} 1.435021{col 58} 16.93261{col 70} 16.98622
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .1047915{col 34} .0333168{col 58} .0394846{col 70} .1700985
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  3.1453
{txt}Ho: diff = 0                                     degrees of freedom = {res}   11011

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.9992         {txt}Pr(|T| > |t|) = {res}0.0017          {txt}Pr(T > t) = {res}0.0008
{txt}
{com}. ttest Sex , by(PART)

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}   8656{col 22} .4691543{col 34} .0053642{col 46} .4990765{col 58} .4586391{col 70} .4796695
       {txt}1 {c |}{res}{col 12}   2360{col 22} .5461864{col 34} .0102505{col 46} .4979678{col 58} .5260855{col 70} .5662874
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12}  11016{col 22} .4856572{col 34} .0047621{col 46} .4998169{col 58} .4763226{col 70} .4949918
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.0770321{col 34}  .011584{col 58}-.0997388{col 70}-.0543254
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -6.6499
{txt}Ho: diff = 0                                     degrees of freedom = {res}   11014

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}1.0000
{txt}
{com}. 
. *RD participation (Table C.4)
. collapse (mean) PART Age_16 Age_18 , by(Birthdate)
{txt}
{com}. rdrobust PART Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1820
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      365{col 34}     1455{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      172{col 34}      172{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  172.715{col 34}  172.715
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  270.280{col 34}  270.280
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.639{col 34}    0.639

Outcome: PART. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .03553{col 33} .04939{col 43}0.7195{col 52}0.472{col 60}-.061266{col 73} .132335
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .0378{col 33} .04939{col 43}0.7654{col 52}0.444{col 60}   -.059{col 73} .134601
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .0378{col 33} .05981{col 43}0.6320{col 52}0.527{col 60}-.079424{col 73} .155025
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust PART Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1820
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}     1092{col 34}      728{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      343{col 34}      345{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  345.286{col 34}  345.286
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  528.748{col 34}  528.748
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.653{col 34}    0.653

Outcome: PART. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.00601{col 33} .02946{col 43}-0.2042{col 52}0.838{col 60}-.063751{col 73} .051722
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.00691{col 33} .02946{col 43}-0.2346{col 52}0.814{col 60}-.064649{col 73} .050825
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.00691{col 33} .03486{col 43}-0.1983{col 52}0.843{col 60}-.075234{col 73}  .06141
{txt}{hline 19}{c BT}{hline 60}

{com}. 
. //Figure C.1
. rdplot PART Age_16 if Age_16>-166&Age_16<166 , c(0) ci(95) shade nbins(166 166) ///
> graph_options(scheme(lean1) legend(off) xlabel(-150(50)150) ylabel(0(0.2)1) title("16-year-olds") ///
> xtitle("Date of birth") name(f1, replace))
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       330
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      165{col 37}      165
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      165{col 37}      165
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  165.000{col 37}  165.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: PART. Running variable: Age_16.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      166{col 37}      166
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.994{col 37}    0.994
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.994{col 37}    0.994
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        8
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       10{col 37}       11
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   33.200{col 37}   20.750
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. rdplot PART Age_18 if Age_18>-318&Age_18<318 , c(0) ci(95) shade nbins(318 318) ///
> graph_options(scheme(lean1) legend(off) xlabel(-300(50)300) ylabel(0(0.2)1) title("18-year-olds") ///
> xtitle("Date of birth") name(f2, replace)) 
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       632
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      315{col 37}      317
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      315{col 37}      317
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  317.000{col 37}  317.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: PART. Running variable: Age_18.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      318{col 37}      318
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.997{col 37}    0.997
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.997{col 37}    0.997
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        7{col 37}        6
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       16{col 37}       17
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   45.429{col 37}   53.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. graph combine f1 f2 , scheme(lean1) xsize(7)
{res}{txt}
{com}. graph export "Figure_C.1.pdf", as(pdf) replace
{txt}(file Figure_C.1.pdf written in PDF format)

{com}. 
. ***Falsiciation analysis (Table C.5)
. *Load data
. use "Data_for_replication.dta" , clear
{txt}
{com}. collapse (mean) Sex Books Expected_education Age_16 Age_18, by(Birthdate)
{txt}
{com}. //16-year-olds
. rdrobust Sex Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1280
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      282{col 34}      998{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       97{col 34}       92{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  124.233{col 34}  124.233
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  187.156{col 34}  187.156
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.664{col 34}    0.664

Outcome: Sex. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .18547{col 33} .14556{col 43}1.2742{col 52}0.203{col 60}-.099827{col 73} .470769
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .20008{col 33} .14556{col 43}1.3745{col 52}0.169{col 60}-.085218{col 73} .485378
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .20008{col 33} .17434{col 43}1.1476{col 52}0.251{col 60}-.141622{col 73} .541783
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Books Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1275
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      280{col 34}      995{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      114{col 34}      109{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  151.857{col 34}  151.857
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  219.846{col 34}  219.846
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.691{col 34}    0.691

Outcome: Books. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.07341{col 33} .31914{col 43}-0.2300{col 52}0.818{col 60}-.698914{col 73} .552094
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.13842{col 33} .31914{col 43}-0.4337{col 52}0.664{col 60}-.763921{col 73} .487088
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.13842{col 33} .37157{col 43}-0.3725{col 52}0.710{col 60}-.866684{col 73} .589851
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Expected_education Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1248
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      274{col 34}      974{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      120{col 34}      114{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  162.459{col 34}  162.459
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  236.103{col 34}  236.103
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.688{col 34}    0.688

Outcome: Expected_education. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.10703{col 33} .46497{col 43}-0.2302{col 52}0.818{col 60}-1.01836{col 73} .804293
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.09927{col 33} .46497{col 43}-0.2135{col 52}0.831{col 60} -1.0106{col 73} .812056
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.09927{col 33} .55956{col 43}-0.1774{col 52}0.859{col 60}-1.19598{col 73}  .99744
{txt}{hline 19}{c BT}{hline 60}

{com}. 
. //18-year-olds
. rdrobust Sex Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1280
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      802{col 34}      478{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      236{col 34}      226{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  331.768{col 34}  331.768
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  516.976{col 34}  516.976
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.642{col 34}    0.642

Outcome: Sex. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.03516{col 33} .09134{col 43}-0.3850{col 52}0.700{col 60}-.214194{col 73} .143866
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.02042{col 33} .09134{col 43}-0.2236{col 52}0.823{col 60}-.199454{col 73} .158607
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.02042{col 33} .11067{col 43}-0.1845{col 52}0.854{col 60}-.237337{col 73}  .19649
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Books Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1275
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      800{col 34}      475{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      141{col 34}      130{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  194.701{col 34}  194.701
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  347.720{col 34}  347.720
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.560{col 34}    0.560

Outcome: Books. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.61679{col 33} .31483{col 43}-1.9591{col 52}0.050{col 60}-1.23383{col 73} .000263
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.73548{col 33} .31483{col 43}-2.3362{col 52}0.019{col 60}-1.35253{col 73}-.118434
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.73548{col 33} .36183{col 43}-2.0327{col 52}0.042{col 60}-1.44465{col 73}-.026312
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust Expected_education Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1248
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      782{col 34}      466{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      200{col 34}      192{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  286.249{col 34}  286.249
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  447.667{col 34}  447.667
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.639{col 34}    0.639

Outcome: Expected_education. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res}-.32012{col 33} .34532{col 43}-0.9270{col 52}0.354{col 60} -.99693{col 73} .356695
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}-.35758{col 33} .34532{col 43}-1.0355{col 52}0.300{col 60} -1.0344{col 73} .319228
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}-.35758{col 33} .41848{col 43}-0.8545{col 52}0.393{col 60} -1.1778{col 73} .462629
{txt}{hline 19}{c BT}{hline 60}

{com}. 
. *** Appendix D ***
. *Load data
. use "Data_for_replication.dta" , clear
{txt}
{com}. *T-tests
. foreach var of varlist Learned_votinglocal Learned_votingnational Learned_laws Learned_rights heardatschool {c -(}
{txt}  2{com}. ttest `var' , by(testgroup)
{txt}  3{com}. {c )-}

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    144{col 22}   1.0625{col 34}  .084329{col 46} 1.011948{col 58} .8958075{col 70} 1.229192
       {txt}1 {c |}{res}{col 12}    112{col 22} 1.357143{col 34} .1060107{col 46} 1.121912{col 58} 1.147075{col 70}  1.56721
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12}    256{col 22} 1.191406{col 34} .0668374{col 46} 1.069398{col 58} 1.059783{col 70}  1.32303
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.2946429{col 34} .1337245{col 58}-.5579929{col 70}-.0312928
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -2.2034
{txt}Ho: diff = 0                                     degrees of freedom = {res}     254

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0142         {txt}Pr(|T| > |t|) = {res}0.0285          {txt}Pr(T > t) = {res}0.9858

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    144{col 22} .7847222{col 34} .0764418{col 46} .9173022{col 58} .6336202{col 70} .9358242
       {txt}1 {c |}{res}{col 12}    113{col 22} .9469027{col 34} .0887481{col 46} .9434048{col 58} .7710598{col 70} 1.122746
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12}    257{col 22} .8560311{col 34} .0580457{col 46} .9305433{col 58} .7417233{col 70}  .970339
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.1621804{col 34} .1167334{col 58}-.3920647{col 70} .0677038
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -1.3893
{txt}Ho: diff = 0                                     degrees of freedom = {res}     255

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.0830         {txt}Pr(|T| > |t|) = {res}0.1659          {txt}Pr(T > t) = {res}0.9170

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    144{col 22} 1.034722{col 34} .0821082{col 46} .9852989{col 58} .8724195{col 70} 1.197025
       {txt}1 {c |}{res}{col 12}    113{col 22} .9513274{col 34} .0893253{col 46} .9495408{col 58} .7743408{col 70} 1.128314
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12}    257{col 22} .9980545{col 34} .0604288{col 46}  .968748{col 58} .8790535{col 70} 1.117055
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0833948{col 34} .1218733{col 58}-.1566115{col 70} .3234011
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  0.6843
{txt}Ho: diff = 0                                     degrees of freedom = {res}     255

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.7528         {txt}Pr(|T| > |t|) = {res}0.4944          {txt}Pr(T > t) = {res}0.2472

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    143{col 22} .8951049{col 34} .0792169{col 46} .9472963{col 58} .7385081{col 70} 1.051702
       {txt}1 {c |}{res}{col 12}    113{col 22} 1.044248{col 34}  .101653{col 46} 1.080587{col 58} .8428353{col 70}  1.24566
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12}    256{col 22} .9609375{col 34} .0630623{col 46} 1.008998{col 58} .8367482{col 70} 1.085127
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22}-.1491429{col 34} .1269049{col 58}-.3990628{col 70}  .100777
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res} -1.1752
{txt}Ho: diff = 0                                     degrees of freedom = {res}     254

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.1205         {txt}Pr(|T| > |t|) = {res}0.2410          {txt}Pr(T > t) = {res}0.8795

{txt}Two-sample t test with equal variances
{hline 9}{c TT}{hline 68}
   Group{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
       0 {c |}{res}{col 12}    149{col 22} .4295302{col 34} .0406895{col 46} .4966786{col 58} .3491228{col 70} .5099376
       {txt}1 {c |}{res}{col 12}    117{col 22} .3675214{col 34} .0447647{col 46} .4842038{col 58} .2788593{col 70} .4561834
{txt}{hline 9}{c +}{hline 68}
combined {c |}{res}{col 12}    266{col 22} .4022556{col 34} .0301221{col 46} .4912773{col 58} .3429465{col 70} .4615648
{txt}{hline 9}{c +}{hline 68}
    diff {c |}{res}{col 22} .0620088{col 34} .0606799{col 58}-.0574694{col 70} .1814871
{txt}{hline 9}{c BT}{hline 68}
    diff = mean({res}0{txt}) - mean({res}1{txt})                                      t = {res}  1.0219
{txt}Ho: diff = 0                                     degrees of freedom = {res}     264

    {txt}Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = {res}0.8461         {txt}Pr(|T| > |t|) = {res}0.3078          {txt}Pr(T > t) = {res}0.1539
{txt}
{com}. 
. *** Appendix E ***
. *Load data
. use "Data_for_replication.dta" , clear
{txt}
{com}. *Collapse data
. collapse (mean) Internal_efficacy External_efficacy Trust Age_16 Age_18 , by(Birthdate)
{txt}
{com}. //Internal political efficacy
. rdplot Internal_efficacy Age_16 if Age_16>-119&Age_16<119 , c(0) ci(95) shade nbins(119 119) ///
> graph_options(scheme(lean1) legend(off) xlabel(-100(50)100) ylabel(0 1) title("16-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f1, replace))
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       179
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}       90{col 37}       89
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}       90{col 37}       89
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  118.000{col 37}  118.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: Internal_efficacy. Running variable: Age_16.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      119{col 37}      119
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.992{col 37}    0.992
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.992{col 37}    0.992
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        4
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}        7{col 37}        7
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   23.800{col 37}   29.750
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. rdplot Internal_efficacy Age_18 if Age_18>-275&Age_18<275 , c(0) ci(95) shade nbins(275 275) ///
> graph_options(scheme(lean1) legend(off) xlabel(-250(250)250) ylabel(0 1) title("18-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f2, replace)) 
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       370
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      187{col 37}      183
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      187{col 37}      183
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  273.000{col 37}  274.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: Internal_efficacy. Running variable: Age_18.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      275{col 37}      275
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.993{col 37}    0.996
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.993{col 37}    0.996
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        4{col 37}        5
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       12{col 37}       10
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   68.750{col 37}   55.000
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. graph combine f1 f2 , scheme(lean1) xsize(7) title("Internal political efficacy" , size(small)) name(F4, replace)
{res}{txt}
{com}. 
. //External political efficacy
. rdplot External_efficacy Age_16 if Age_16>-124&Age_16<124 , c(0) ci(95) shade nbins(124 124) ///
> graph_options(scheme(lean1) legend(off) xlabel(-100(50)100) ylabel(0 1) title("16-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f1, replace))
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       183
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}       93{col 37}       90
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}       93{col 37}       90
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  123.000{col 37}  122.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: External_efficacy. Running variable: Age_16.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      124{col 37}      124
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.992{col 37}    0.984
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.992{col 37}    0.984
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        3{col 37}        3
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}        9{col 37}        6
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   41.333{col 37}   41.333
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. rdplot External_efficacy Age_18 if Age_18>-241&Age_18<241 , c(0) ci(95) shade nbins(241 241) ///
> graph_options(scheme(lean1) legend(off) xlabel(-250(250)250) ylabel(0 1) title("18-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f2, replace)) 
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       325
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      165{col 37}      160
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      165{col 37}      160
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  240.000{col 37}  239.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: External_efficacy. Running variable: Age_18.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      241{col 37}      241
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.996{col 37}    0.992
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.996{col 37}    0.992
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        6{col 37}        3
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       12{col 37}        8
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   40.167{col 37}   80.333
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. graph combine f1 f2 , scheme(lean1) xsize(7) title("External political efficacy" , size(small)) name(F5, replace)
{res}{txt}
{com}.                 
. //Political trust
. rdplot Trust Age_16 if Age_16>-172&Age_16<172 , c(0) ci(95) shade nbins(172 172) ///
> graph_options(scheme(lean1) legend(off) xlabel(-150(50)150) ylabel(0 1) title("16-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f1, replace))
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       243
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      126{col 37}      117
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      126{col 37}      117
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  171.000{col 37}  169.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: Trust. Running variable: Age_16.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      172{col 37}      172
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.994{col 37}    0.983
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.994{col 37}    0.983
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        2{col 37}        5
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}        9{col 37}        8
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   86.000{col 37}   34.400
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. rdplot Trust Age_18 if Age_18>-201&Age_18<201 , c(0) ci(95) shade nbins(201 201) ///
> graph_options(scheme(lean1) legend(off) xlabel(-200(100)200) ylabel(0 1) title("18-year-olds", size(medsmall)) ///
> xtitle("Date of birth") name(f2, replace)) 
{res}
RD Plot with RD plot with manually set number of bins.

{txt}{ralign 21: Cutoff c = 0}{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c{col 54}{txt}Number of obs  = {res}       266
{txt}{hline 22}{c +}{hline 22}{col 54}Kernel         = {res}{ralign 10:Uniform}
{txt}{ralign 21:Number of obs}{col 22} {c |} {col 23}{res}      136{col 37}      130
{txt}{ralign 21:Eff. Number of obs}{col 22} {c |} {col 23}{res}      136{col 37}      130
{txt}{ralign 21:Order poly. fit (p)}{col 22} {c |} {col 23}{res}        4{col 37}        4
{txt}{ralign 21:BW poly. fit (h)}{col 22} {c |} {col 23}{res}  200.000{col 37}  200.000
{txt}{ralign 21:Number of bins scale}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000

Outcome: Trust. Running variable: Age_18.
{txt}{hline 22}{c TT}{hline 22}
{col 22} {c |} {col 23}Left of {res}c{col 36}{txt}Right of {res}c
{txt}{hline 22}{c +}{hline 22}
{ralign 21:Bins selected}{col 22} {c |} {col 23}{res}      201{col 37}      201
{txt}{ralign 21:Average bin length}{col 22} {c |} {col 23}{res}    0.995{col 37}    0.995
{txt}{ralign 21:Median bin length}{col 22} {c |} {col 23}{res}    0.995{col 37}    0.995
{txt}{hline 22}{c +}{hline 22}
{ralign 21:IMSE-optimal bins}{col 22} {c |} {col 23}{res}        5{col 37}        5
{txt}{ralign 21:Mimicking Var. bins}{col 22} {c |} {col 23}{res}       10{col 37}        9
{txt}{hline 22}{c +}{hline 22}
{lalign 1:Rel. to IMSE-optimal:}{col 22} {c |} 
{ralign 21:Implied scale}{col 22} {c |} {col 23}{res}   40.200{col 37}   40.200
{txt}{ralign 21:WIMSE var. weight}{col 22} {c |} {col 23}{res}    0.000{col 37}    0.000
{txt}{ralign 21:WIMSE bias weight}{col 22} {c |} {col 23}{res}    1.000{col 37}    1.000
{txt}{hline 22}{c BT}{hline 22}

{res}{txt}
{com}. graph combine f1 f2 , scheme(lean1) xsize(7) title("Political trust" , size(small)) name(F6, replace)
{res}{txt}
{com}.                 
. //Create Figure E.1
. graph combine F4 F5 F6 , scheme(lean1) col(1) ysize(10)
{res}{txt}
{com}. //Export
. graph export "Figure_E.1.pdf", as(pdf) replace
{txt}(file Figure_E.1.pdf written in PDF format)

{com}. 
. *** Appendix F ***
. *Load data
. use "Data_for_replication.dta" , clear
{txt}
{com}. *Collapse data
. collapse (mean) Attention_politics_general Internal_efficacy Age_16 Age_18 , by(Birthdate)
{txt}
{com}. *Attention to politics
. //16-year-olds
. rdrobust Attention_politics_general Age_16 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1278
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      281{col 34}      997{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}       79{col 34}       75{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  101.646{col 34}  101.646
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  183.662{col 34}  183.662
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.553{col 34}    0.553

Outcome: Attention_politics_general. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .13678{col 33} .06341{col 43}2.1571{col 52}0.031{col 60}   .0125{col 73} .261053
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .16519{col 33} .06341{col 43}2.6053{col 52}0.009{col 60} .040918{col 73} .289471
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .16519{col 33} .07102{col 43}2.3260{col 52}0.020{col 60} .025998{col 73}  .30439
{txt}{hline 19}{c BT}{hline 60}

{com}. est clear
{txt}
{com}. foreach num of numlist 45(5)180 {c -(}
{txt}  2{com}. quietly rdrobust Attention_politics_general Age_16 , c(0) all h(`num')
{txt}  3{com}. est store m_`num'
{txt}  4{com}. {c )-}
{txt}
{com}. coefplot m_* , drop(Conventional Robust) scheme(lean1) vertical yline(0) legend(off) msymbol(o) title("") xtitle("Bandwidth")   ///
> ylabel(0(0.25)0.5) xlabel(0.525 "45" 0.9975 "90" 1.47 "180") xline(0.9975 , lpattern(shortdash))
{res}{txt}
{com}. graph export "Figure_F.1.pdf", as(pdf) replace
{txt}(file Figure_F.1.pdf written in PDF format)

{com}. 
. //18-year-olds
. rdrobust Attention_politics_general Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1278
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      802{col 34}      476{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      167{col 34}      160{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  235.909{col 34}  235.909
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  417.069{col 34}  417.069
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.566{col 34}    0.566

Outcome: Attention_politics_general. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .11794{col 33} .06318{col 43}1.8666{col 52}0.062{col 60}-.005896{col 73} .241776
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res}  .1394{col 33} .06318{col 43}2.2063{col 52}0.027{col 60} .015565{col 73} .263238
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res}  .1394{col 33} .07272{col 43}1.9169{col 52}0.055{col 60}-.003134{col 73} .281937
{txt}{hline 19}{c BT}{hline 60}

{com}. est clear
{txt}
{com}. foreach num of numlist 117(11)470 {c -(}
{txt}  2{com}. quietly rdrobust Attention_politics_general Age_18 , c(0) all h(`num')
{txt}  3{com}. est store m_`num'
{txt}  4{com}. {c )-}
{txt}
{com}. coefplot m_* , drop(Conventional Robust) scheme(lean1) vertical yline(0) legend(off) msymbol(o) title("") xtitle("Bandwidth")   ///
> ylabel(0(0.1)0.3) xlabel(0.525 "117" 0.9975 "235" 1.47 "470") xline(0.9975 , lpattern(shortdash))
{res}{txt}
{com}. graph export "Figure_F.2.pdf", as(pdf) replace
{txt}(file Figure_F.2.pdf written in PDF format)

{com}. 
. *18-year-olds internal efficacy
. rdrobust Internal_efficacy Age_18 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1251
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      786{col 34}      465{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      187{col 34}      183{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}  274.586{col 34}  274.586
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  460.201{col 34}  460.201
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.597{col 34}    0.597

Outcome: Internal_efficacy. Running variable: Age_18.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .10128{col 33} .04627{col 43}2.1888{col 52}0.029{col 60} .010589{col 73} .191968
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .11545{col 33} .04627{col 43}2.4950{col 52}0.013{col 60} .024756{col 73} .206135
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .11545{col 33} .05411{col 43}2.1337{col 52}0.033{col 60}   .0094{col 73} .221491
{txt}{hline 19}{c BT}{hline 60}

{com}. est clear
{txt}
{com}. foreach num of numlist 162(18)646 {c -(}
{txt}  2{com}. quietly rdrobust Internal_efficacy Age_18 , c(0) all h(`num')
{txt}  3{com}. est store m_`num'
{txt}  4{com}. {c )-}
{txt}
{com}. coefplot m_* , drop(Conventional Robust) scheme(lean1) vertical yline(0) legend(off) msymbol(o) title("") xtitle("Bandwidth")   ///
> ylabel(0(0.1)0.2) xlabel(0.525 "162" 0.9975 "290" 1.47 "646") xline(0.9975 , lpattern(shortdash))
{res}{txt}
{com}. graph export "Figure_F.3.pdf", as(pdf) replace
{txt}(file Figure_F.3.pdf written in PDF format)

{com}. 
. *** Appendix G ***
. *Load data
. use "Data_for_replication.dta" , clear
{txt}
{com}. *Generated collapsed variables based on voted or non-voted
. bysort Birthdate: egen meanvoted=mean(Attention_politics_general) if testvoted==1
{txt}(1494 missing values generated)

{com}. bysort Birthdate: egen meannotvoted=mean(Attention_politics_general) if testnotvoted==1
{txt}(1204 missing values generated)

{com}. *Analyses
. rdrobust meanvoted Age_16 if testvoted==1 , c(0) all 
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}       866
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      573{col 34}      293{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      117{col 34}       32{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}   70.735{col 34}   70.735
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  153.830{col 34}  153.830
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.460{col 34}    0.460

Outcome: meanvoted. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .20435{col 33} .07446{col 43}2.7443{col 52}0.006{col 60} .058406{col 73} .350295
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .24448{col 33} .07446{col 43}3.2832{col 52}0.001{col 60} .098535{col 73} .390423
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .24448{col 33} .08193{col 43}2.9842{col 52}0.003{col 60} .083908{col 73}  .40505
{txt}{hline 19}{c BT}{hline 60}

{com}. rdrobust meannotvoted Age_16 if testnotvoted==1 , c(0) all
{res}
Sharp RD estimates using local polynomial regression.

{txt}{ralign 18: Cutoff c = 0}{col 19} {c |} {col 21}Left of {res}c{col 33}{txt}Right of {res}c{col 55}{txt}Number of obs = {res}      1156
{txt}{hline 19}{c +}{hline 22}{col 55}BW type       = {res}{ralign 10:mserd}
{txt}{ralign 18:Number of obs}{col 19} {c |} {col 21}{res}      573{col 34}      583{col 55}{txt}Kernel        = {res}{ralign 10:Triangular}
{txt}{ralign 18:Eff. Number of obs}{col 19} {c |} {col 21}{res}      136{col 34}       72{col 55}{txt}VCE method    = {res}{ralign 10:NN}
{txt}{ralign 18:Order est. (p)}{col 19} {c |} {col 21}{res}        1{col 34}        1
{txt}{ralign 18:Order bias (q)}{col 19} {c |} {col 21}{res}        2{col 34}        2
{txt}{ralign 18:BW est. (h)}{col 19} {c |} {col 21}{res}   81.217{col 34}   81.217
{txt}{ralign 18:BW bias (b)}{col 19} {c |} {col 21}{res}  160.512{col 34}  160.512
{txt}{ralign 18:rho (h/b)}{col 19} {c |} {col 21}{res}    0.506{col 34}    0.506

Outcome: meannotvoted. Running variable: Age_16.
{txt}{hline 19}{c TT}{hline 60}
{ralign 18:Method}{col 19} {c |} {col 24}Coef.{col 33}Std. Err.{col 46}z{col 52}P>|z|{col 61}[95% Conf. Interval]
{hline 19}{c +}{hline 60}
{ralign 18:Conventional}{col 19} {c |} {col 22}{res} .11586{col 33} .04845{col 43}2.3914{col 52}0.017{col 60} .020905{col 73} .210825
{txt}{ralign 18:Bias-corrected}{col 19} {c |} {col 22}{res} .13932{col 33} .04845{col 43}2.8756{col 52}0.004{col 60} .044364{col 73} .234284
{txt}{ralign 18:Robust}{col 19} {c |} {col 22}{res} .13932{col 33} .05297{col 43}2.6301{col 52}0.009{col 60} .035499{col 73} .243149
{txt}{hline 19}{c BT}{hline 60}

{com}. 
. 
{txt}end of do-file

{com}. 